Computer graphics
Ten lectures on wavelets
Characterization of Signals from Multiscale Edges
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image organization and retrieval with automatically constructed feature vectors
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Wavelets for computer graphics: theory and applications
Wavelets for computer graphics: theory and applications
Filtering for Texture Classification: A Comparative Study
IEEE Transactions on Pattern Analysis and Machine Intelligence
Statistical Pattern Recognition: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
PicSOM—content-based image retrieval with self-organizing maps
Pattern Recognition Letters - Selected papers from the 11th scandinavian conference on image analysis
Self-Organizing Maps
Textural Features for Image Database Retrieval
CBAIVL '98 Proceedings of the IEEE Workshop on Content - Based Access of Image and Video Libraries
Medical image retrieval using texture, locality and colour
CLEF'04 Proceedings of the 5th conference on Cross-Language Evaluation Forum: multilingual Information Access for Text, Speech and Images
IEEE Transactions on Information Technology in Biomedicine
Design and analysis of a content-based pathology image retrieval system
IEEE Transactions on Information Technology in Biomedicine
The JPEG2000 still image coding system: an overview
IEEE Transactions on Consumer Electronics
Statistical texture characterization from discrete wavelet representations
IEEE Transactions on Image Processing
Texture analysis and classification with tree-structured wavelet transform
IEEE Transactions on Image Processing
Guest Editorial: Intelligent data analysis in biomedicine
Journal of Biomedical Informatics
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Biological interpretation of morphological patterns in histopathological whole-slide images
Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine
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In medical image analysis the image content is often represented by features computed from the pixel matrix in order to support the development of improved clinical diagnosis systems. These features need to be interpreted and understood at a clinical level of understanding Many features are of abstract nature, as for instance features derived from a wavelet transform. The interpretation and analysis of such features are difficult. This lack of coincidence between computed features and their meaning for a user in a given situation is commonly referred to as the semantic gap. In this work, we propose a method for feature analysis and interpretation based on the simultaneous visualization of feature and image domain. Histopathological images of meningiomas WHO (World Health Organization) grade I are represented by features derived from color transforms and the Discrete Wavelet Transform. The wavelet-based feature space is then visualized and explored using unsupervised machine learning methods. We show how to analyze and select features according to their relevance for the description of clinically relevant characteristics.